Lymphoma

Synthesizing images of tau pathology from cross-modal neuroimaging using deep learning.

Given the prevalence of dementia and the development of pathology-specific disease-modifying therapies, high-value biomarker strategies to inform medical decision-making are critical. In vivo tau-PET is an ideal target as a biomarker for Alzheimer's disease diagnosis and treatment outcome measure. However, tau-PET is not currently widely accessible to patients compared to other neuroimaging method...

Comparison of machine learning models to predict complications of bariatric surgery: A systematic review.

Due to changes in lifestyle, bariatric surgery is expanding worldwide. However, this surgery has numerous complications, and early identification of these complications could be essential in assisting patients to have a higher-quality surgery. Machine learning has a significant role in prediction tasks. So far, no systematic review has been carried out on leveraging ML techniques for predicting c...

Binary fire hawks optimizer with deep learning driven non-invasive diabetes detection and classification.

Non-invasive diabetes detection refers to the utilization and development of technologies and methods that can monitor and diagnose diabetes without r...

Application of Machine-learning based on Radiomics Features in Differential Diagnosis of Superficial Lymphadenopathy.

OBJECTIVE: The accurate diagnosis of superficial lymphadenopathy is challenging. We aim to explore a non-invasive and accurate machine-learning method...

CT-based intratumoral and peritumoral deep transfer learning features prediction of lymph node metastasis in non-small cell lung cancer.

BACKGROUND: The main metastatic route for lung cancer is lymph node metastasis, and studies have shown that non-small cell lung cancer (NSCLC) has a h...

Bridging artificial intelligence and fucoxanthin for the recovery and quantification from microalgae.

Fucoxanthin is a carotenoid that possesses various beneficial medicinal properties for human well-being. However, the current extraction technologies ...

Skin Changes in Suspected Lyme Disease.

Dear Editor, Ticks carry many diseases, bacteria, and viruses and represent a very important healthcare issue both in Croatia and globally. Although m...

scDeepInsight: a supervised cell-type identification method for scRNA-seq data with deep learning.

Annotation of cell-types is a critical step in the analysis of single-cell RNA sequencing (scRNA-seq) data that allows the study of heterogeneity acro...

A deep learning model based on the combination of convolutional and recurrent neural networks to enhance pulse oximetry ability to classify sleep stages in children with sleep apnea.

Characterization of sleep stages is essential in the diagnosis of sleep-related disorders but relies on manual scoring of overnight polysomnography (P...

The Influence of Brain MRI Defacing Algorithms on Brain-Age Predictions via 3D Convolutional Neural Networks.

In brain imaging research, it is becoming standard practice to remove the face from the individual's 3D structural MRI scan to ensure data privacy sta...

Artificial Intelligence Assisted Multi-modal Photoacoustic-Ultrasound Imaging for Studying Renal Tissue Function and Hemodynamics.

Combined functional-anatomic imaging modalities, which integrate the benefits of visualizing gross anatomy along with the functional or metabolic info...

Radiomics in colorectal cancer patients.

The main therapeutic options for colorectal cancer are surgical resection and adjuvant chemotherapy in non-metastatic disease. However, the evaluation...

Simulation and prediction of the attenuation behaviour of the KNN-LMN-based lead-free ceramics by FLUKA code and artificial neural network (ANN)-based algorithm.

The significance and novelty of the present work are the preparation of the non-lead ceramic by the general formula of (1-x) KNa.NbO-xLa MnNiO (KNN-LM...

AIM-CICs: an automatic identification method for cell-in-cell structures based on convolutional neural network.

Edited by Luonan Chen Whereas biochemical markers are available for most types of cell death, current studies on non-autonomous cell death by entosis ...

HLAncPred: a method for predicting promiscuous non-classical HLA binding sites.

Human leukocyte antigens (HLA) regulate various innate and adaptive immune responses and play a crucial immunomodulatory role. Recent studies revealed...

Ultrasonographic morphological characteristics determined using a deep learning-based computer-aided diagnostic system of breast cancer.

To investigate the correlations between ultrasonographic morphological characteristics quantitatively assessed using a deep learning-based computer-ai...

Artificial Intelligence in Lymphoma PET Imaging:: A Scoping Review (Current Trends and Future Directions).

Malignant lymphomas are a family of heterogenous disorders caused by clonal proliferation of lymphocytes. F-FDG-PET has proven to provide essential in...

Impact feature recognition method for non-stationary signals based on variational modal decomposition noise reduction and support vector machine optimized by whale optimization algorithm.

It is difficult to effectively distinguish the key information of non-stationary dynamic signals in many engineering applications, such as fault detec...

[Comparison of single incision robot-assisted laparoscopic radical prostatectomy with and without extraperitoneal special channel device].

To compare the clinical effects of single-incision robot-assisted laparoscopic radical prostatectomy (RARP) with and without extraperitoneal special ...

Automatic Deep Learning Segmentation and Quantification of Epicardial Adipose Tissue in Non-Contrast Cardiac CT scans.

An Automatic deep learning semantic segmentation (ADLS) using DeepLab-v3-plus technique is proposed for a full and accurate whole heart Epicardial adi...